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基于立体视觉的三维接池监测和透状态识别可变间隙钥匙孔青惰性气体接
Zishun Wang1, Yonghua Shi1, Yanxin Cui2
1School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, China.
Sensors (Basel, Switzerland)
|December 17, 2024
概括
这项研究引入了用于Keyhole Tungsten Inert Gas (K-TIG) 接的视觉传感方法,以监测接池几何和组装间隙. 精确的透状态识别,对于接质量至关重要,通过专注于隙宽度,以96.7%的准确度实现.
科学领域:
- 材料科学 材料科学 材料科学
- 制造业 工程 制造工程
- 机器人和自动化机器人与自动化
背景情况:
- 钥匙孔惰气 (K-TIG) 接对于中厚板材至关重要,但接质量取决于稳定的透.
- 工件中的组装缺口往往会破坏K-TIG接透的稳定性.
- 与弧电压或声学传感相比,视觉传感提供了优越的池几何特征提取.
研究的目的:
- 使用立体视觉系统开发K-TIG接的3D接池监控算法.
- 为了识别和量化中等/厚板组装间隙.
- 建立一个强大的透状态识别模型,以改善K-TIG接质量控制.
主要方法:
- 用一个单个高动态范围 (HDR) 摄像头的语义细分网络用于3D池监控.
- 开发了一个基于流域的算法来提取组装间隙宽度.
- 使用3D接池特征和间隙宽度构建了一个透状态识别模型,通过特征切除实验验验证.
主要成果:
- 该研究确定了组装间隙宽度是准确透识别的最关键特征.
- 接池面积被发现会对透识别精度产生负面影响.
- 开发的透识别模型在排除面积特征后,达到96.7%的高精度.
结论:
- 一种新的视觉传感方法有效地监测K-TIG接池几何和组装间隙.
- 间隙宽度是K-TIG接中透稳定性的关键决定因素.
- 拟议的模型显著提高了透状态识别精度,为改善接自动化和质量铺平了道路.
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